Recommendation Setup & Feeds
The catalog behind a recommendation — feeds, interests, filters and fallbacks.
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Tuning the Engine — Score Blend & Presets
The account-wide weights behind every recommendation ordering — purchases vs views, freshness, click feedback, and the per-visitor price range that stays off unless you switch it on.
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Setting the Product / Content Feed for Recommendations
Product/Content Catalog Setup **We are using product data in this example for convenience only; the content feed has the same functionality and structure. Setting up your product catalog will allow:…
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Setting Filters On Recommendations
Filter the pool of products or content that recommendation algorithms draw from — by category, price range, stock status, brand, or any custom attribute — for sharper, more relevant recommendations.
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Setting Recommendation Fallbacks
Configure fallback algorithms on Personyze recommendations so visitors with no behavioral data — new subscribers, anonymous traffic — never see empty or random recommendations.
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Reviewing the Data Behind Recommendations
Personyze recommendations are not only powerful in what they can output to users to increase engagement and revenue, but also in the data you can derive from them, to learn…
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Recommendations as JSON — Where to Start
While you don't need to do any coding to implement Personyze recommendations across your site and emails, some clients may wish to use their own display method from their CMS,…
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Interests for Recommendations
Interests apply to all types of websites, ranging from e-commerce and content curation platforms to news sites and educational portals.